IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v13y2016i6p562-d71471.html
   My bibliography  Save this article

Health-Care Waste Treatment Technology Selection Using the Interval 2-Tuple Induced TOPSIS Method

Author

Listed:
  • Chao Lu

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Jian-Xin You

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Hu-Chen Liu

    (School of Management, Shanghai University, Shanghai 200444, China
    School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Ping Li

    (Zhoupu Hospital Affiliated to Shanghai University of Medicine & Health Sciences, Shanghai 201318, China)

Abstract

Health-care waste (HCW) management is a major challenge for municipalities, particularly in the cities of developing nations. Selecting the best treatment technology for HCW can be regarded as a complex multi-criteria decision making (MCDM) issue involving a number of alternatives and multiple evaluation criteria. In addition, decision makers tend to express their personal assessments via multi-granularity linguistic term sets because of different backgrounds and knowledge, some of which may be imprecise, uncertain and incomplete. Therefore, the main objective of this study is to propose a new hybrid decision making approach combining interval 2-tuple induced distance operators with the technique for order preference by similarity to an ideal solution (TOPSIS) for tackling HCW treatment technology selection problems with linguistic information. The proposed interval 2-tuple induced TOPSIS (ITI-TOPSIS) can not only model the uncertainty and diversity of the assessment information given by decision makers, but also reflect the complex attitudinal characters of decision makers and provide much more complete information for the selection of the optimum disposal alternative. Finally, an empirical example in Shanghai, China is provided to illustrate the proposed decision making method, and results show that the ITI-TOPSIS proposed in this paper can solve the problem of HCW treatment technology selection effectively.

Suggested Citation

  • Chao Lu & Jian-Xin You & Hu-Chen Liu & Ping Li, 2016. "Health-Care Waste Treatment Technology Selection Using the Interval 2-Tuple Induced TOPSIS Method," IJERPH, MDPI, vol. 13(6), pages 1-16, June.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:6:p:562-:d:71471
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/13/6/562/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/13/6/562/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Manli Wang & Haiqing Fang & Ghose Bishwajit & Yuanxi Xiang & Hang Fu & Zhanchun Feng, 2015. "Evaluation of Rural Primary Health Care in Western China: A Cross-Sectional Study," IJERPH, MDPI, vol. 12(11), pages 1-18, October.
    2. Yi-Xi Xue & Jian-Xin You & Xufeng Zhao & Hu-Chen Liu, 2016. "An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information," International Journal of Production Research, Taylor & Francis Journals, vol. 54(18), pages 5452-5467, September.
    3. Shuping Sang & Zhenkun Wang & Chuanhua Yu, 2014. "Evaluation of Health Care System Reform in Hubei Province, China," IJERPH, MDPI, vol. 11(2), pages 1-16, February.
    4. Brent, Alan C. & Rogers, David E.C. & Ramabitsa-Siimane, Tsaletseng S.M. & Rohwer, Mark B., 2007. "Application of the analytical hierarchy process to establish health care waste management systems that minimise infection risks in developing countries," European Journal of Operational Research, Elsevier, vol. 181(1), pages 403-424, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sheng-Li Si & Xiao-Yue You & Hu-Chen Liu & Jia Huang, 2017. "Identifying Key Performance Indicators for Holistic Hospital Management with a Modified DEMATEL Approach," IJERPH, MDPI, vol. 14(8), pages 1-17, August.
    2. Xiayu Tong & Zhou-Jing Wang, 2016. "A Group Decision Framework with Intuitionistic Preference Relations and Its Application to Low Carbon Supplier Selection," IJERPH, MDPI, vol. 13(9), pages 1-16, September.
    3. Wuyong Qian & Zhou-Jing Wang & Kevin W. Li, 2016. "Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations," IJERPH, MDPI, vol. 13(9), pages 1-13, September.
    4. Adis Puška & Željko Stević & Dragan Pamučar, 2022. "Evaluation and selection of healthcare waste incinerators using extended sustainability criteria and multi-criteria analysis methods," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 11195-11225, September.
    5. Torkayesh, Ali Ebadi & Rajaeifar, Mohammad Ali & Rostom, Madona & Malmir, Behnam & Yazdani, Morteza & Suh, Sangwon & Heidrich, Oliver, 2022. "Integrating life cycle assessment and multi criteria decision making for sustainable waste management: Key issues and recommendations for future studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Md. Sohrab Hossain & Nik Norulaini Nik Ab Rahman & Venugopal Balakrishnan & Vignesh R. Puvanesuaran & Md. Zaidul Islam Sarker & Mohd Omar Ab Kadir, 2013. "Infectious Risk Assessment of Unsafe Handling Practices and Management of Clinical Solid Waste," IJERPH, MDPI, vol. 10(2), pages 1-12, January.
    2. Brandenburg, Marcus & Govindan, Kannan & Sarkis, Joseph & Seuring, Stefan, 2014. "Quantitative models for sustainable supply chain management: Developments and directions," European Journal of Operational Research, Elsevier, vol. 233(2), pages 299-312.
    3. Liu, Hu-Chen & You, Xiao-Yue & Xue, Yi-Xi & Luan, Xue, 2017. "Exploring critical factors influencing the diffusion of electric vehicles in China: A multi-stakeholder perspective," Research in Transportation Economics, Elsevier, vol. 66(C), pages 46-58.
    4. Xiaoli Tian & Zeshui Xu & Xinxin Wang & Jing Gu & Fawaz E. Alsaadi, 2019. "Decision Models to Find a Promising Start-Up Firm with Qualiflex under Probabilistic Linguistic Circumstance," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1379-1402, July.
    5. Ke-Qin Wang & Hu-Chen Liu & Liping Liu & Jia Huang, 2017. "Green Supplier Evaluation and Selection Using Cloud Model Theory and the QUALIFLEX Method," Sustainability, MDPI, vol. 9(5), pages 1-17, April.
    6. E.K. Broughton & A.C. Brent & L. Haywood, 2012. "Application of a Multi-Criteria Analysis Approach for Decision-Making in the Energy Sector: The Case of Concentrating Solar Power in South Africa," Energy & Environment, , vol. 23(8), pages 1221-1231, December.
    7. Oriyomi Modupe Okeyinka & Rana Khan & Chaminda Pathirage & Charf El Dine Mahammedi & Antony West, 2023. "A Critical Review of Developers’ Decision Criteria for Brownfield Regeneration: Development of the BRIC Index," Sustainability, MDPI, vol. 15(9), pages 1-25, April.
    8. Lorena Pradenas & Marco Fuentes & Víctor Parada, 2020. "Optimizing waste storage areas in health care centers," Annals of Operations Research, Springer, vol. 295(1), pages 503-516, December.
    9. Worawej Onnom & Nitin Tripathi & Vilas Nitivattananon & Sarawut Ninsawat, 2018. "Development of a Liveable City Index (LCI) Using Multi Criteria Geospatial Modelling for Medium Class Cities in Developing Countries," Sustainability, MDPI, vol. 10(2), pages 1-19, February.
    10. Garbuzova-Schlifter, Maria & Madlener, Reinhard, 2016. "AHP-based risk analysis of energy performance contracting projects in Russia," Energy Policy, Elsevier, vol. 97(C), pages 559-581.
    11. Konidari, Popi & Mavrakis, Dimitrios, 2007. "A multi-criteria evaluation method for climate change mitigation policy instruments," Energy Policy, Elsevier, vol. 35(12), pages 6235-6257, December.
    12. Abderrahmen Mediouni & Nicolas Zufferey & Nachiappan Subramanian & Naoufel Cheikhrouhou, 2019. "Fit between humanitarian professionals and project requirements: hybrid group decision procedure to reduce uncertainty in decision-making," Annals of Operations Research, Springer, vol. 283(1), pages 471-496, December.
    13. Sheng-Li Si & Xiao-Yue You & Hu-Chen Liu & Jia Huang, 2017. "Identifying Key Performance Indicators for Holistic Hospital Management with a Modified DEMATEL Approach," IJERPH, MDPI, vol. 14(8), pages 1-17, August.
    14. Liu, Hu-Chen & Li, Zhaojun & Zhang, Jian-Qing & You, Xiao-Yue, 2018. "A large group decision making approach for dependence assessment in human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 135-144.
    15. Wei Xu & Tao Sun, 2022. "Evaluation of rural habitat environment in under-developed areas of Western China: a case study of Northern Shaanxi," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 10503-10539, September.
    16. Zhi Zeng & Wenjuan Tao & Shanlong Ding & Jianlong Fang & Jin Wen & Jianhong Yao & Wei Zhang, 2022. "Horizontal Integration and Financing Reform of Rural Primary Care in China: A Model for Low-Resource and Remote Settings," IJERPH, MDPI, vol. 19(14), pages 1-12, July.
    17. Adam Senetra & Katarzyna Pawlewicz & Adam Pawlewicz, 2019. "The Dynamics of Changes and Spatial Differences in the Synthetic Indicator for Evaluating Environmental Performance in Poland: Current State," IJERPH, MDPI, vol. 16(22), pages 1-23, November.
    18. Zhou, Pengfei & Luo, Jie & Cheng, Fei & Yüksel, Serhat & Dinçer, Hasan, 2021. "Analysis of risk priorities for renewable energy investment projects using a hybrid IT2 hesitant fuzzy decision-making approach with alpha cuts," Energy, Elsevier, vol. 224(C).
    19. Da Feng & Ray Serrano & Ting Ye & Shangfeng Tang & Lei Duan & Yuan Xu & Jian Yang & Yuan Liang & Shanquan Chen & Zhanchun Feng & Liang Zhang, 2016. "What Contributes to the Regularity of Patients with Hypertension or Diabetes Seeking Health Services? A Pilot Follow-Up, Observational Study in Two Sites in Hubei Province, China," IJERPH, MDPI, vol. 13(12), pages 1-14, December.
    20. Liu, Hu-Chen & You, Jian-Xin & Lu, Chao & Chen, Yi-Zeng, 2015. "Evaluating health-care waste treatment technologies using a hybrid multi-criteria decision making model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 932-942.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:13:y:2016:i:6:p:562-:d:71471. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.